1. Introduction to Artificial Intelligence

2. What is AI?

3. How do we classify research as AI?

4. Intelligence The ability to learn and to cope. The ability to learn and to cope. The ability to contemplate, think, and reason. The ability to contemplate, think, and reason. Synonyms: Synonyms:  Brain, brainpower, mentality, mother wit, sense, wit Related: Related:  Acumen, discernment (ayırıcılık, duyarlılık), insight, judgment (yargı), perspicacity, sagacity (sağduyu), wisdom (bilgelik)

5. Intelligence Turing Test: A human communicates with a computer via a teletype. If the human can’t tell he is talking to a computer or another human, it passes. Turing Test: A human communicates with a computer via a teletype. If the human can’t tell he is talking to a computer or another human, it passes.  Natural language processing  knowledge representation  automated reasoning  machine learning Add vision and robotics to get the total Turing test. Add vision and robotics to get the total Turing test.

6. Weak and Strong AI Claims Weak AI: Weak AI:  Machines can be made to act as if they were intelligent. Strong AI: Strong AI:  Machines that act intelligently have real, conscious minds.

7. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

8. Search “All AI is search” “All AI is search”  Game theory  Problem spaces Every problem is a feature space of all possible (successful or unsuccessful) solutions. Every problem is a feature space of all possible (successful or unsuccessful) solutions. The trick is to find an efficient search strategy. The trick is to find an efficient search strategy.

9. Search: Game Theory 9!+1 = 362,880

10. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

11. Learning Explanation Explanation  Discovery  Data Mining No Explanation No Explanation  Neural Nets  Case Based Reasoning

12. Learning: Explanation Cases to rules Cases to rules

13. Learning: No Explanation Neural nets Neural nets

14. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

16. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

17. Rule-Based Systems Logic Languages Logic Languages  Prolog, Lisp Knowledge bases Knowledge bases Inference engines Inference engines

18. Rule-Based Languages: Prolog Father(abraham, isaac).Male(isaac). Father(haran, lot).Male(lot). Father(haran, milcah).Female(milcah). Father(haran, yiscah).Female(yiscah). Son(X,Y)  Father(Y,X), Male(X). Daughter(X,Y)  Father(Y,X), Female(X). Son(lot, haran)?

19. Rule Based Systems KRS KRS

20. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

21. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

22. Ability-Based Areas Computer vision Computer vision Natural language recognition Natural language recognition Natural language generation Natural language generation Speech recognition Speech recognition Speech generation Speech generation Robotics Robotics

23. Natural Language: Translation “The flesh is weak, but the spirit is strong”  Translate to Russian  Translate back to English “The food was lousy, but the vodka was great!”

24. Natural Language Recognition

25. “Tom believes Mary wants to marry a sailor.”

26. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

27. Approaches to AI Searching Searching Learning Learning From Natural to Artificial Systems From Natural to Artificial Systems Knowledge Representation and Reasoning Knowledge Representation and Reasoning Expert Systems and Planning Expert Systems and Planning Communication, Perception, Action Communication, Perception, Action

28. What is Intelligence? The Chinese Room The Chinese Room

29. What is Intelligence? The Chinese Room The Chinese Room

30. What is Intelligence? Replacing the brain? Replacing the brain?

31. Face Recognition Example Take three regular photos from different sides of a human face Take three regular photos from different sides of a human face Generate a digital model of the human face Generate a digital model of the human face Uses of the work: Uses of the work:  Medical applications: Aesthetic operations  Hair dresser and friseur works  Animations to use in movie industry  Etc.

32. Results

35. How far have we got? Our best systems have the intelligence of a frog Our best systems have the intelligence of a frog

36. What is Artificial Intelligence? We will find out … We will find out …

37. Interesting webpages http://aima.cs.berkeley.edu/demos.html http://aima.cs.berkeley.edu/demos.html http://lslwww.epfl.ch/~anperez/BlackJack/cl asses/RLJavaBJ.html http://lslwww.epfl.ch/~anperez/BlackJack/cl asses/RLJavaBJ.html